


'''simple docstring'''






import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__UpperCAmelCase       							=				get_tests_dir('''fixtures/test_sentencepiece.model''')




@require_sentencepiece
@require_tokenizers
class 						a__							(				a__							,							unittest.TestCase    ):





							'''simple docstring'''






							lowercase__     :  List[Any]      		= XLMRobertaTokenizer
							lowercase__     :  Optional[Any]      		= XLMRobertaTokenizerFast
							lowercase__     :  Union[str, Any]      		= True
							lowercase__     :  List[str]      		= True







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				List[Any]:
														super().setUp()

														# We have a SentencePiece fixture for testing
														lowerCAmelCase__			  =      XLMRobertaTokenizer(lowerCamelCase_   ,       keep_accents=lowerCamelCase_  )
														tokenizer.save_pretrained(self.tmpdirname  )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Any:
														lowerCAmelCase__			  =      '''<pad>'''
														lowerCAmelCase__			  =      1

														self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase_  )   ,       lowerCamelCase_  )
														self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase_  )   ,       lowerCamelCase_  )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Any:
														lowerCAmelCase__			  =      list(self.get_tokenizer().get_vocab().keys()  )

														self.assertEqual(vocab_keys[0]   ,       '''<s>'''  )
														self.assertEqual(vocab_keys[1]   ,       '''<pad>'''  )
														self.assertEqual(vocab_keys[-1]   ,       '''<mask>'''  )
														self.assertEqual(len(lowerCamelCase_  )   ,       10_02  )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				int:
														self.assertEqual(self.get_tokenizer().vocab_size   ,       10_02  )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Optional[int]:
														lowerCAmelCase__			  =      XLMRobertaTokenizer(lowerCamelCase_   ,       keep_accents=lowerCamelCase_  )

														lowerCAmelCase__			  =      tokenizer.tokenize('''This is a test'''  )
														self.assertListEqual(lowerCamelCase_   ,       ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']  )

														self.assertListEqual(
														    tokenizer.convert_tokens_to_ids(lowerCamelCase_  )   ,       [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]   ,       )

														lowerCAmelCase__			  =      tokenizer.tokenize('''I was born in 92000, and this is falsé.'''  )
														self.assertListEqual(
														    lowerCamelCase_   ,       [
														        SPIECE_UNDERLINE + '''I''',
														        SPIECE_UNDERLINE + '''was''',
														        SPIECE_UNDERLINE + '''b''',
														        '''or''',
														        '''n''',
														        SPIECE_UNDERLINE + '''in''',
														        SPIECE_UNDERLINE + '''''',
														        '''9''',
														        '''2''',
														        '''0''',
														        '''0''',
														        '''0''',
														        ''',''',
														        SPIECE_UNDERLINE + '''and''',
														        SPIECE_UNDERLINE + '''this''',
														        SPIECE_UNDERLINE + '''is''',
														        SPIECE_UNDERLINE + '''f''',
														        '''al''',
														        '''s''',
														        '''é''',
														        '''.''',
														    ]   ,       )
														lowerCAmelCase__			  =      tokenizer.convert_tokens_to_ids(lowerCamelCase_  )
														self.assertListEqual(
														    lowerCamelCase_   ,       [
														        value + tokenizer.fairseq_offset
														        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
														        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
														    ]   ,       )

														lowerCAmelCase__			  =      tokenizer.convert_ids_to_tokens(lowerCamelCase_  )
														self.assertListEqual(
														    lowerCamelCase_   ,       [
														        SPIECE_UNDERLINE + '''I''',
														        SPIECE_UNDERLINE + '''was''',
														        SPIECE_UNDERLINE + '''b''',
														        '''or''',
														        '''n''',
														        SPIECE_UNDERLINE + '''in''',
														        SPIECE_UNDERLINE + '''''',
														        '''<unk>''',
														        '''2''',
														        '''0''',
														        '''0''',
														        '''0''',
														        ''',''',
														        SPIECE_UNDERLINE + '''and''',
														        SPIECE_UNDERLINE + '''this''',
														        SPIECE_UNDERLINE + '''is''',
														        SPIECE_UNDERLINE + '''f''',
														        '''al''',
														        '''s''',
														        '''<unk>''',
														        '''.''',
														    ]   ,       )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Tuple:
														if not self.test_slow_tokenizer:
																					# as we don't have a slow version, we can't compare the outputs between slow and fast versions
																					return

														lowerCAmelCase__			  =      (self.rust_tokenizer_class, '''hf-internal-testing/tiny-xlm-roberta''', {})
														for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																					with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""  ):
																												lowerCAmelCase__			  =      self.rust_tokenizer_class.from_pretrained(lowerCamelCase_   ,       **lowerCamelCase_  )
																												lowerCAmelCase__			  =      self.tokenizer_class.from_pretrained(lowerCamelCase_   ,       **lowerCamelCase_  )

																												lowerCAmelCase__			  =      tempfile.mkdtemp()

																												lowerCAmelCase__			  =      tokenizer_r.save_pretrained(lowerCamelCase_  )
																												lowerCAmelCase__			  =      tokenizer_p.save_pretrained(lowerCamelCase_  )

																												# Checks it save with the same files + the tokenizer.json file for the fast one
																												self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files  )  )
																												lowerCAmelCase__			  =      tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f  )
																												self.assertSequenceEqual(lowerCamelCase_   ,       lowerCamelCase_  )

																												# Checks everything loads correctly in the same way
																												lowerCAmelCase__			  =      tokenizer_r.from_pretrained(lowerCamelCase_  )
																												lowerCAmelCase__			  =      tokenizer_p.from_pretrained(lowerCamelCase_  )

																												# Check special tokens are set accordingly on Rust and Python
																												for key in tokenizer_pp.special_tokens_map:
																																			self.assertTrue(hasattr(lowerCamelCase_   ,       lowerCamelCase_  )  )
																																			# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																																			# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																												shutil.rmtree(lowerCamelCase_  )

																												# Save tokenizer rust, legacy_format=True
																												lowerCAmelCase__			  =      tempfile.mkdtemp()

																												lowerCAmelCase__			  =      tokenizer_r.save_pretrained(lowerCamelCase_   ,       legacy_format=lowerCamelCase_  )
																												lowerCAmelCase__			  =      tokenizer_p.save_pretrained(lowerCamelCase_  )

																												# Checks it save with the same files
																												self.assertSequenceEqual(lowerCamelCase_   ,       lowerCamelCase_  )

																												# Checks everything loads correctly in the same way
																												lowerCAmelCase__			  =      tokenizer_r.from_pretrained(lowerCamelCase_  )
																												lowerCAmelCase__			  =      tokenizer_p.from_pretrained(lowerCamelCase_  )

																												# Check special tokens are set accordingly on Rust and Python
																												for key in tokenizer_pp.special_tokens_map:
																																			self.assertTrue(hasattr(lowerCamelCase_   ,       lowerCamelCase_  )  )

																												shutil.rmtree(lowerCamelCase_  )

																												# Save tokenizer rust, legacy_format=False
																												lowerCAmelCase__			  =      tempfile.mkdtemp()

																												lowerCAmelCase__			  =      tokenizer_r.save_pretrained(lowerCamelCase_   ,       legacy_format=lowerCamelCase_  )
																												lowerCAmelCase__			  =      tokenizer_p.save_pretrained(lowerCamelCase_  )

																												# Checks it saved the tokenizer.json file
																												self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files  )  )

																												# Checks everything loads correctly in the same way
																												lowerCAmelCase__			  =      tokenizer_r.from_pretrained(lowerCamelCase_  )
																												lowerCAmelCase__			  =      tokenizer_p.from_pretrained(lowerCamelCase_  )

																												# Check special tokens are set accordingly on Rust and Python
																												for key in tokenizer_pp.special_tokens_map:
																																			self.assertTrue(hasattr(lowerCamelCase_   ,       lowerCamelCase_  )  )

																												shutil.rmtree(lowerCamelCase_  )







							@cached_property
							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Tuple:
														return XLMRobertaTokenizer.from_pretrained('''xlm-roberta-base'''  )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Optional[int]:
														with tempfile.NamedTemporaryFile() as f:
																					shutil.copyfile(lowerCamelCase_   ,       f.name  )
																					lowerCAmelCase__			  =      XLMRobertaTokenizer(f.name   ,       keep_accents=lowerCamelCase_  )
																					lowerCAmelCase__			  =      pickle.dumps(lowerCamelCase_  )
														pickle.loads(lowerCamelCase_  )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Optional[int]:
														if not self.test_rust_tokenizer:
																					return

														lowerCAmelCase__			  =      self.get_tokenizer()
														lowerCAmelCase__			  =      self.get_rust_tokenizer()

														lowerCAmelCase__			  =      '''I was born in 92000, and this is falsé.'''

														lowerCAmelCase__			  =      tokenizer.tokenize(lowerCamelCase_  )
														lowerCAmelCase__			  =      rust_tokenizer.tokenize(lowerCamelCase_  )
														self.assertListEqual(lowerCamelCase_   ,       lowerCamelCase_  )

														lowerCAmelCase__			  =      tokenizer.encode(lowerCamelCase_   ,       add_special_tokens=lowerCamelCase_  )
														lowerCAmelCase__			  =      rust_tokenizer.encode(lowerCamelCase_   ,       add_special_tokens=lowerCamelCase_  )
														self.assertListEqual(lowerCamelCase_   ,       lowerCamelCase_  )

														lowerCAmelCase__			  =      self.get_rust_tokenizer()
														lowerCAmelCase__			  =      tokenizer.encode(lowerCamelCase_  )
														lowerCAmelCase__			  =      rust_tokenizer.encode(lowerCamelCase_  )
														self.assertListEqual(lowerCamelCase_   ,       lowerCamelCase_  )







							@slow
							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Optional[int]:
														lowerCAmelCase__			  =      '''Hello World!'''
														lowerCAmelCase__			  =      [0, 3_53_78, 66_61, 38, 2]
														# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
														# xlmr.eval()
														# xlmr.encode(symbols)

														self.assertListEqual(lowerCamelCase_   ,       self.big_tokenizer.encode(lowerCamelCase_  )  )







							@slow
							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Union[str, Any]:
														lowerCAmelCase__			  =      (
														    '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
														    ''' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'''
														)
														lowerCAmelCase__			  =      [
														    0,
														    32_93,
														    83,
														    10,
														    45_52,
														    49_89,
														    79_86,
														    6_78,
														    10,
														    59_15,
														    1_11,
														    17_94_59,
														    12_48_50,
														    4,
														    60_44,
														    2_37,
														    12,
														    6,
														    5,
														    6,
														    4,
														    67_80,
														    7_05,
														    15,
														    13_88,
														    44,
														    3_78,
														    1_01_14,
														    7_11,
														    1_52,
														    20,
														    6,
														    5,
														    2_23_76,
														    6_42,
														    12_21,
														    1_51_90,
														    3_41_53,
														    4_50,
														    56_08,
														    9_59,
														    11_19,
														    5_77_02,
														    1_36,
														    1_86,
														    47,
														    10_98,
														    2_93_67,
														    47,
														    # 4426, # What fairseq tokenizes from "<unk>": "_<"
														    # 3678, # What fairseq tokenizes from "<unk>": "unk"
														    # 2740, # What fairseq tokenizes from "<unk>": ">"
														    3,  # What we tokenize from "<unk>": "<unk>"
														    6,  # Residue from the tokenization: an extra sentencepiece underline
														    4,
														    60_44,
														    2_37,
														    62_84,
														    5_09_01,
														    5_28,
														    31,
														    90,
														    34,
														    9_27,
														    2,
														]
														# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
														# xlmr.eval()
														# xlmr.encode(symbols)

														self.assertListEqual(lowerCamelCase_   ,       self.big_tokenizer.encode(lowerCamelCase_  )  )







							@slow
							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Optional[Any]:
														# fmt: off
														lowerCAmelCase__			  =      {'''input_ids''': [[0, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [0, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
														# fmt: on

														self.tokenizer_integration_test_util(
														    expected_encoding=lowerCamelCase_   ,       model_name='''xlm-roberta-base'''   ,       revision='''d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'''   ,       )





'''simple docstring'''


from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
UpperCAmelCase_					=   Lock()


def     SCREAMING_SNAKE_CASE							(   a_						:				str					,       a_						:				Tuple					,       a_						:				Dict					,       a_						:				Optional[Any]					,       a_						:				str					,       a_						:				Any					,       a_						:				Optional[Any]      ):
  global process_lock

  # we perform n swaps since after n swaps we know we are sorted
  # we *could* stop early if we are sorted already, but it takes as long to
  # find out we are sorted as it does to sort the list with this algorithm
  for i in range(0					,       10      ):
    if (i + position) % 2 == 0 and r_send is not None:
      # send your value to your right neighbor
      process_lock.acquire()
      r_send[1].send(a_      )
      process_lock.release()

      # receive your right neighbor's value
      process_lock.acquire()
      __a								=       rr_cv[0].recv()
      process_lock.release()

      # take the lower value since you are on the left
      __a								=       min(a_					,       a_      )
    elif (i + position) % 2 != 0 and l_send is not None:
      # send your value to your left neighbor
      process_lock.acquire()
      l_send[1].send(a_      )
      process_lock.release()

      # receive your left neighbor's value
      process_lock.acquire()
      __a								=       lr_cv[0].recv()
      process_lock.release()

      # take the higher value since you are on the right
      __a								=       max(a_					,       a_      )
    # after all swaps are performed, send the values back to main
  result_pipe[1].send(a_      )


def     SCREAMING_SNAKE_CASE							(   a_						:				List[str]      ):
  __a								=       []
  __a								=       []
  # initialize the list of pipes where the values will be retrieved
  for _ in arr:
    result_pipe.append(Pipe()      )
  # creates the processes
  # the first and last process only have one neighbor so they are made outside
  # of the loop
  __a								=       Pipe()
  __a								=       Pipe()
  process_array_.append(
      Process(
          target=a_					,       args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])					,       )      )
  __a								=       temp_rs
  __a								=       temp_rr

  for i in range(1					,       len(a_      ) - 1      ):
    __a								=       Pipe()
    __a								=       Pipe()
    process_array_.append(
        Process(
            target=a_					,       args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])					,       )      )
    __a								=       temp_rs
    __a								=       temp_rr

  process_array_.append(
      Process(
          target=a_					,       args=(
              len(a_      ) - 1,
              arr[len(a_      ) - 1],
              temp_ls,
              None,
              temp_lr,
              None,
              result_pipe[len(a_      ) - 1],
          )					,       )      )

  # start the processes
  for p in process_array_:
    p.start()

  # wait for the processes to end and write their values to the list
  for p in range(0					,       len(a_      )      ):
    __a								=       result_pipe[p][0].recv()
    process_array_[p].join()
  return arr


def     SCREAMING_SNAKE_CASE							(   ):
  __a								=       list(range(10					,       0					,       -1      )      )
  print('Initial List'      )
  print(*a_      )
  __a								=       odd_even_transposition(a_      )
  print('Sorted List\n'      )
  print(*a_      )


if __name__ == "__main__":
  main()



